{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "c8658b12",
   "metadata": {},
   "outputs": [],
   "source": [
    "#导入模块\n",
    "import torch\n",
    "from spikingjelly.activation_based import neuron\n",
    "from spikingjelly import visualizing\n",
    "from matplotlib import pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e84ac735",
   "metadata": {},
   "outputs": [],
   "source": [
    "#新建一个IF神经元层\n",
    "if_layer = neuron.IFNode()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7ee2196",
   "metadata": {},
   "source": [
    "IF神经元层有一些构造参数，在API文档中对这些参数有详细的解释，我们暂时只关注下面几个重要的参数：\n",
    "+ v_threshold – 神经元的阈值电压\n",
    "+ v_reset – 神经元的重置电压。如果不为 None，当神经元释放脉冲后，电压会被重置为 v_reset；如果设置为 None，则电压会被减去 v_threshold\n",
    "+ surrogate_function – 反向传播时用来计算脉冲函数梯度的替代函数\n",
    "\n",
    "对于 spikingjelly.activation_based.neuron.IFNode 中的绝大多数神经元层，神经元的数量是在初始化或调用 reset() 函数重新初始化后，根据第一次接收的输入的 shape 自动决定的。\n",
    "\n",
    "与RNN中的神经元非常类似，脉冲神经元也是有状态的，或者说是有记忆。脉冲神经元的状态变量，一般是它的膜电位 。因此，spikingjelly.activation_based.neuron 中的神经元，都有成员变量 v。可以打印出刚才新建的IF神经元层的膜电位："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "fe4beebf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.0\n"
     ]
    }
   ],
   "source": [
    "print(if_layer.v)\n",
    "# if_layer.v=0.0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6568656a",
   "metadata": {},
   "source": [
    "可以发现，现在的 if_layer.v 是 0.0，因为我们还没有给与它任何输入。我们给与几个不同的输入，观察神经元的电压的 shape，可以发现它与输入的数量是一致的："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "54665b62",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x.shape=torch.Size([2, 3]), if_layer.v.shape=torch.Size([2, 3])\n",
      "x.shape=torch.Size([4, 5, 6]), if_layer.v.shape=torch.Size([4, 5, 6])\n"
     ]
    }
   ],
   "source": [
    "x = torch.rand(size=[2, 3])\n",
    "if_layer(x)\n",
    "print(f'x.shape={x.shape}, if_layer.v.shape={if_layer.v.shape}')\n",
    "# x.shape=torch.Size([2, 3]), if_layer.v.shape=torch.Size([2, 3])\n",
    "if_layer.reset()\n",
    "\n",
    "x = torch.rand(size=[4, 5, 6])\n",
    "if_layer(x)\n",
    "print(f'x.shape={x.shape}, if_layer.v.shape={if_layer.v.shape}')\n",
    "# x.shape=torch.Size([4, 5, 6]), if_layer.v.shape=torch.Size([4, 5, 6])\n",
    "if_layer.reset()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d1ced62",
   "metadata": {},
   "source": [
    "脉冲神经元是有状态的，在输入下一个样本前，一定要先调用 reset() 函数清除之前的状态。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca9dc73d",
   "metadata": {},
   "source": [
    "可以在 spikingjelly.activation_based.neuron.IFNode.neuronal_charge 中找到如下所示的代码，表明脉冲神经元中，vt不仅取决于当前时刻的输入，也取决于上一个时刻末的膜电位："
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f325e64c",
   "metadata": {},
   "source": [
    "def neuronal_charge(self, x: torch.Tensor):  \n",
    "    self.v = self.v + x"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f7dcac2b",
   "metadata": {},
   "source": [
    "不同的神经元，充电方程不尽相同。但膜电位超过阈值电压后，释放脉冲，以及释放脉冲后，膜电位的重置都是相同的。因此它们全部继承自 spikingjelly.activation_based.neuron.BaseNode，共享相同的放电、重置方程。可以在 spikingjelly.activation_based.neuron.BaseNode.neuronal_fire 中找到释放脉冲的代码"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4aba92bb",
   "metadata": {},
   "source": [
    "def neuronal_fire(self):  \n",
    "    self.spike = self.surrogate_function(self.v - self.v_threshold)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48644051",
   "metadata": {},
   "source": [
    "surrogate_function() 在前向传播时是阶跃函数，只要输入大于或等于0，就会返回1，否则会返回0。我们将这种元素仅为0或1的 tensor 视为脉冲。\n",
    "\n",
    "释放脉冲消耗了神经元之前积累的电荷，因此膜电位会有一个瞬间的降低，即膜电位的重置。在SNN中，对膜电位重置的实现，有2种方式：\n",
    "\n",
    "Hard方式：释放脉冲后，膜电位直接被设置成重置电压：\n",
    "\n",
    "Soft方式：释放脉冲后，膜电位减去阈值电压：\n",
    "\n",
    "可以发现，对于使用Soft方式的神经元，并不需要重置电压  这个变量。spikingjelly.activation_based.neuron 中的神经元，在构造函数的参数之一 v_reset，默认为 1.0 ，表示神经元使用Hard方式；若设置为 None，则会使用Soft方式。在 spikingjelly.activation_based.neuron.BaseNode.neuronal_fire.neuronal_reset 中可以找到膜电位重置的代码："
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc8e0ffc",
   "metadata": {},
   "source": [
    "The following codes are for tutorials. The actual codes are different, but have the similar behavior.\n",
    "\n",
    "def neuronal_reset(self):  \n",
    "    if self.v_reset is None:  \n",
    "        self.v = self.v - self.spike * self.v_threshold  \n",
    "    else:  \n",
    "        self.v = (1. - self.spike) * self.v + self.spike *   self.v_reset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45e77337",
   "metadata": {},
   "source": [
    "接下来，我们将逐步给与神经元输入，并查看它的膜电位和输出脉冲。\n",
    "\n",
    "现在让我们给与IF神经元层持续的输入，并画出其放电后的膜电位和输出脉冲："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cb13e8e2",
   "metadata": {},
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 3600x2400 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if_layer.reset()\n",
    "x = torch.as_tensor([0.02])\n",
    "T = 150\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(if_layer(x))\n",
    "    v_list.append(if_layer.v)\n",
    "\n",
    "dpi = 300\n",
    "figsize = (12, 8)\n",
    "visualizing.plot_one_neuron_v_s(torch.cat(v_list).numpy(), torch.cat(s_list).numpy(), v_threshold=if_layer.v_threshold,\n",
    "                                v_reset=if_layer.v_reset,\n",
    "                                figsize=figsize, dpi=dpi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "906988ef",
   "metadata": {},
   "source": [
    "我们给与的输入 shape=[1]，因此这个IF神经元层只有1个神经元。它的膜电位和输出脉冲随着时间变化情况如上\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6c8de05",
   "metadata": {},
   "source": [
    "下面我们将神经元层重置，并给与 shape=[32] 的输入，查看这32个神经元的膜电位和输出脉冲："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "ddc62a99",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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A1qUZdfImhm/q27eq7h7gj6GF62jguW35x8AXx/n7eUdVXTrzYUkTtgj4RJLjaRJNv6OZGnUNms+4uzB808AdwJuq6h7T7VXVpUkOAPYFNgVOT/LR9lwb0HxOfnJb/eNV9dsZ/Ym00Cxi+m34liRvp/mbvh5wTvvZ4mxgFWAHYG+akaxLgT0cba1lhf05zXf25yRp4uJn0IUnyYuAI4E1x6hyKfCCqrps9qKSJibJY2mmAt6wp9phNJ1sR1prViQ5HHjtROu30+90j98d+NIkL7tfVS2a5DHSqKbbhttzBPhPmhu47rW/407gvVV1wCTDlEaVZLIdmt9X1aOmcJ3FNF/0T+l4aSydtjWeK4HXV9XJY5xnOeALwOt7zvFF4M1+CapBGlQbbs+1F83niZXGqHILsGtVnTTGfmngkiyiuckbmqlTTxmxf3fsz2kZNl4bbuvYn5OkCXCk6gJUVd9K8gSa/yRfADyc5m7Ry4CvAZ+uqr/1nEKaM1V1STutzp7Ay4F/BO5HM1XU6cAhVeVawJI0y9rRInsnORJ4I/Bsmi9YV6P5AvQy4FSav9OOEpSkYdsA2wLPoVmKZV3ggcBtwNU0U+t9Gziur5/WJkrf0I4WfDOwGc3MA9cC59D8/f3uzP0YWsAG0oYBquozSU4B9gK2Ax4G3AVcDnwPOLCqrpqRn0KSFjD7c5I0MY5UlSRJkiRJkiRJkqQey41fRZIkSZIkSZIkSZIWLpOqkiRJkiRJkiRJktTDpKokSZIkSZIkSZIk9TCpKkmSJEmSJEmSJEk9TKpKkiRJkiRJkiRJUg+TqpIkSZIkSZIkSZLUw6SqJEmSJEmSJEmSJPUwqSpJkiRJkiRJkiRJPUyqSpIkSZIkSZIkSVIPk6qSJEmSJEmSJEmS1MOkqiRJkiRJkiRJkiT1MKkqSZIkSZIkSZIkST1MqkqSJEmSJEmSJElSD5OqkiRJkiRJkiRJktTDpKokSZIkSZIkSZIk9TCpKkmSJEmSJEmSJEk9TKpKkiRJC0SSxUkqyeFzHcsgJNm9/XkqyaOWgXhOaWM5Za5jkSRJkiRJg2VSVZIkSZIkSZIkSZJ6mFSVJEmSpDEkObwdfbp4rmOZL5a1EcSSJEmSJA3CCnMdgCRJkqTZUVWPmusY7suqauu5jkGSJEmSJM0MR6pKkiRJkiRJkiRJUg+TqpIkSZIkSZIkSZLUw6SqJEmSNM8keWiSjyQ5L8lNSe5I8uckv05ydLum5ZqjHLe4Xefy8FH2bd1ZB3PrNN6Q5GdJrkvylyRnJ3nNiONWSrJHkjOTXJ/k5iSnJ3llT/z3uNY4P+tQvUUTfX86xy6X5J+THNDGdG2SO5PcmORX7fZHjnHsoiQFvLbdtF4nlr8/RhxzSrv9lFHO96jOcbu327ZL8q32d3d7kiuSHJzk4RP42dZO8vEklya5NcnVSU5OsmO7fyDrmibZMcmJSa5sY7w5yeVJTkvyoSRP69Tdun1PvtQ5xRWjvG9bj3Gt7ZIc2b4Pt7Zt7vwkH0vykJ4YF3V/H0nWSrJfkouS3NK2y1OS7DLV90GSJEmSJNdUlSRJkuaRJFsA3wZGJk3XbR8bA68Grm3rTcWKwEnAi0Zs3wz4SpJNq+odSe4PnAhsOaLe5sDmSTasqv2nGMMg/F/gA6Ns/wfgie1jzyS7VtUJsxlYko8A+4zY/ChgD+BlSbaqqkvGOPaJwMnAOp3NqwDbAtsm+TxwxjTjWx44GnjFiF0rAfcD1geeDewAbDrNa60OHAHsOGLXKsAT2seeSXaqqt42nWR9mvdmg87m1YGtgK2S/AuwU1UtnU7MkiRJkqSFx6SqJEmSNE8kWRk4hiahejNwMPATYAlNInQ94JnAy6Z5qQ8BTwe+ChwF/Bn4J2AR8Bjg7Um+BbyNJoF6MHACcB3wpPb4hwIfTHJSVV00zXimagXgqja2M4DLgduAR9DE/VaaBOFRSZ4yIon5WeDrwIeBlwB/ArYfUFxvaq9/KnAIcCmwFrBb+1gHOIzmd3kPbSL7ewwnVL8KHAlcA2wIvAN4M03CeDr2ZDih+jPgUOB3wC3AA2iS9zu05SHnAJvQvF8fbrdtT/PedV3R+XmWB74FPAcomvb9jbbOisDTgH8DHgkcn2TzqvpFT9zH0iR8P0fz+7uJJim7D00bfjlNm3j7+G+BJEmSJEnDTKpKkiRJ88ezaJKVADuPMmrvLOC4JO8GVpvGdZ4OvLOqPtXZdl47re1vaJK6RwFrAy+tqhNH1DsX+CWwPE2C7x3TiGU6DgX2q6o7R2w/DzgpyUHAmcDDgPcCf5/auKqWAEuS3NhuurOqLhxQXJsDXwDeUlXdKYR/lOQO4I3AM5I8uap+OeLYRcCD2/K/V9UnOvt+keTrwPE0ic3pGJq++SzgOaOM7Pwx8F9J/p5Uraq/Ahcm6Y5cvbSqFvdc5500CdU7gZdU1XdH7D8zyRHAacDjgQOBLXrOtxnNv42jO9vOTfK19hxPBPZK8oWq+nXPeSRJkiRJugfXVJUkSZLmjwd3yj8dq1JVLa2qv0zjOmeNSKgOnffPNKM+oRkpeeyIhOpQvQtoRjdCfwJsRlXV4lESqt39VwIfb1++OElmJzKuAt42IqE65IBO+R7vXZJVGF7j9TzgP0ceXFV3AW+hGZE7HUNt7ed9U+VW1fVTvUCSFWlGoQJ8epSE6tA1bgDe3b58dpINe0777REJ1aFz3EyT4IemH7zH1KKWJEmSJC1UJlUlSZKk+eOqTvl1M3idY3r2XdApH9tT7/z2+dHTD2cwkqyZZP0kj0+ycZKNgb+1u9ekmTZ2Nny9qm4fbUdV/YZmil2493v3VJr1YAG+MkZSlqq6Gvj+NGMcamsvSrL2NM81lqcBD2nLx41Tt3sTwb2mRe740lg7qupsYGgq6m3HjU6SJEmSpA6TqpIkSdL88TOadUEBDkxydpL3JNk8yUoDvM6lPftunGS9NaYbzHQkWS/JQUkW06yveTlwIfDr9vH5TvWZSh6O9N/j7L+hfR753m3cKfetKwpw7qQiurcvt88bApclOSzJTkkePs3zdnWnCT4jSY31YDjRDPccsT3SOeNc8+z2+R8H/G9GkiRJknQfZ1JVkiRJmifaqWxfBFzSbtoM2B84HbgxyXeT7Jxk+Wle6m89++6eZL0563Mk2QG4GPhXYL0JHLLqzEb0d33vGwy/dyN/j/fvlJeMc45rJhXRCFV1GE3bWkozOvZ1NOvo/iHJZUkOSDLdUcgPmuJxfesFj/e+XN0+h3u+n5IkSZIk9TKpKkmSJM0jVXUxsAmwI3AY8Lt216rA84CvAmclmWrC6j4hyQNpkoCr0YxyXEQzbeyDgJWrKlUVYJvuYbMd57Ksqt5HM1L1fcCPGU4Gb0CzFup/J5nO2qTdpPHWNO16Io+D+8Ie55r+jiVJkiRJU7LCXAcgSZIkaXKq6i7gxPZBkocAOwBvpVl386nAITSJ12VRd7TrmDd6Jll9Gtd4BbBWW35pVZ08Rr35NFrxhk75QfRPv7zOIC5YVb+nGbG6f5IVadZBfQXwFmAV4LNJzqqqX07h9Nd1yndU1YXTDhjWBf7Qs3/oZoPinu+nJEmSJEm9HKkqSZIkzXNVdVU7XeszgfPazS9MMlvT2U7WzZ1yX1LzMdO4xuPb5+t7Eqpwz3U9RzPeyMfZdFGnPF7c4+2ftKq6s6pOr6p3Aju3mwO8fGTVCZ6ym4h97jTDG7LZBPf/tqruGNA1JUmSJEkLgElVSZIk6T6iXXP11PblCgyP1FzWXNEp9yX/du7ZN56hWXlWTjJqvyfJasBu45zntqHzTCOWQTkXuKktvybJqFPZJlkX2H6GY/lRp7z2iH23dcp979vPgOvb8h5J1hxAXK8da0eSTYGN25c/HMC1JEmSJEkLiElVSZIkaZ5IskWSDXv2rwRs1b68BbhmVgKbpKq6Ebigffm6JA8YWSfJlsDbp3GZ37bPq3PvkZQkWR44FHjoOOe5qn1+UJI1phHPtFXVbcBX2pdPAd41sk6bQD6EZmreKUuya5K+5WK6I0uvGLHvqk55g7FO0P48B7QvHwwc0zflc5I1kvxrT0wAL07yylGOvR/w+fbl3TTvkSRJkiRJE+aaqpIkSdL8sQ3w/iSnAd+hSUxeA6wK/BOwB02yDeDQqlo6J1FOzGeBz9GsgXlakg8BvwEeALwQ2JNmZOYzp3j+42jWAl0ZODzJk2hGJ/6FZmrgt9GsPXs68Kye8/y8fV4O+FySg2jWAi2AqrpsivFN1SKaNU0fDByQ5MnAETTtYEPgHcDmwNk065/C1KYwPqI9/zdo3oPf0YxAXRfYjub3A03y/sgRx/6yrbsK8KEkS4HFDK+l+8equrUtf4ymXW9Dsy7wxUk+B5wB3AisQTMN9NbAv7Tn/XRP3OcCRyXZCvg6ze/7CcA+DE8n/ZmqumCM4yVJkiRJGpVJVUmSJGl+WY5mNOpWPXW+AbxndsKZsi8Az6NJlD0OOHrE/guBlwF/msrJq+rKJHvSjEZdleb9GPmeHNvG0TcV7I+BM4Fn0ExHPHJK4lGn4J0pVXV9kucBJwPrALu0j67DgdMYTqrextSsS5M83XOM/TcCr6qqK0fEeHOS/wL+D02S//sjjnsOcEpb964kL6JJsO8GPJImGT6WJePE/EqaqYnf2j5GOp5RRvhKkiRJkjQep/+VJEmS5o+PAc8HPkmT6PsfmoTZbTQjAY8FXlBVL2unVl1mVdXdNNPy7gWcA/y1fVwAvA94elVdNfYZJnSNLwFbACfSjOS8k2Zq2u/RJANfDdw1gTifC3wYOJ9mZOZURn4OTFWdT5OI/gTNNMe3A9cCPwF2rqrXAd31SW+610nGtxHNaN4TgYtpRucuBW6gaXuLgMdU1Q/GOH5f4E00yd3r6Xmfq+rWqnotzfq6BwMXtTEvpUnc/gr4Ik17eWxf0FV1Bc0I5P2BS4C/tef6KbBrVb18GR/BLUmSJElaRqVqTr8PkCRJkiQNWJJDgTcAV1bVI+Y6npmUZBHwAYCqmtWRw5IkSZKkhcORqpIkSZJ0H5JkVeAl7csz5zIWSZIkSZLuK0yqSpIkSdI8kmSDJKOOyEyyPM0Uumu3m748a4FJkiRJknQftsJcByBJkiRJmpT3A09LcgxwFrAEWBV4As06pk9p6/0I+M6cRChJkiRJ0n2MSVVJkiRJmn8eC+zXs/904FVVVbMUjyRJkiRJ92kmVSVJkiRpfvn/wKXAdsB6wDrAisB1wLnAscAxVXX3nEUoSZIkSdJ9TLxxWZIkSZIkSZIkSZLGttxcByBJkiRJkiRJkiRJyzKTqpIkSZIkSZIkSZLUw6SqJEmSJEmSJEmSJPUwqSpJkiRJkiRJkiRJPUyqSpIkSZIkSZIkSVIPk6qSJEmSJEmSJEmS1MOkqiRJkiRJkiRJkiT1MKkqSZIkSZIkSZIkST1MqkqSJEmSJEmSJElSD5OqkiRJkiRJkiRJktTDpKokSZIkSZIkSZIk9TCpKkmSJEmSJEmSJEk9TKpKkiRJkiRJkiRJUg+TqpIkSZIkSZIkSZLUw6SqJEmSJEmSJEmSJPUwqSpJkiRJkiRJkiRJPUyqSpIkSZIkSZIkSVIPk6qSJEmSJEmSJEmS1MOkqiRJkiRJkiRJkiT1+F/kguBbuzqW/wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 2400x1600 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2400x1600 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "if_layer.reset()\n",
    "T = 50\n",
    "x = torch.rand([32]) / 8.\n",
    "s_list = []\n",
    "v_list = []\n",
    "for t in range(T):\n",
    "    s_list.append(if_layer(x).unsqueeze(0))\n",
    "    v_list.append(if_layer.v.unsqueeze(0))\n",
    "\n",
    "s_list = torch.cat(s_list)\n",
    "v_list = torch.cat(v_list)\n",
    "\n",
    "figsize = (12, 8)\n",
    "dpi = 200\n",
    "visualizing.plot_2d_heatmap(array=v_list.numpy(), title='membrane potentials', xlabel='simulating step',\n",
    "                            ylabel='neuron index', int_x_ticks=True, x_max=T, figsize=figsize, dpi=dpi)\n",
    "\n",
    "\n",
    "visualizing.plot_1d_spikes(spikes=s_list.numpy(), title='membrane sotentials', xlabel='simulating step',\n",
    "                        ylabel='neuron index', figsize=figsize, dpi=dpi)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3898927",
   "metadata": {},
   "source": [
    "步进模式和后端"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3d6edea",
   "metadata": {},
   "source": [
    "在基本概念中我们已经介绍过单步和多步模式，在本教程前面的内容中，我们使用的都是单步模式。切换成多步模式非常简单，只需要设置 step_mode 即可："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "108526ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "from spikingjelly.activation_based import neuron, functional\n",
    "if_layer = neuron.IFNode(step_mode='s')\n",
    "T = 8\n",
    "N = 2\n",
    "x_seq = torch.rand([T, N])\n",
    "y_seq = functional.multi_step_forward(x_seq, if_layer)\n",
    "if_layer.reset()\n",
    "\n",
    "if_layer.step_mode = 'm'\n",
    "y_seq = if_layer(x_seq)\n",
    "if_layer.reset()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52e569bf",
   "metadata": {},
   "source": [
    "此外，部分神经元在多步模式下支持 cupy 后端。在 cupy 模式下，前反向传播会使用CuPy进行加速："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9a5c4b21",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "if_layer.backend=torch\n",
      "step_mode=s, supported_backends=('torch',)\n",
      "step_mode=m, supported_backends=('torch', 'cupy')\n",
      "if_layer.backend=cupy\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "from spikingjelly.activation_based import neuron\n",
    "if_layer = neuron.IFNode()\n",
    "print(f'if_layer.backend={if_layer.backend}')\n",
    "# if_layer.backend=torch\n",
    "\n",
    "print(f'step_mode={if_layer.step_mode}, supported_backends={if_layer.supported_backends}')\n",
    "# step_mode=s, supported_backends=('torch',)\n",
    "\n",
    "\n",
    "if_layer.step_mode = 'm'\n",
    "print(f'step_mode={if_layer.step_mode}, supported_backends={if_layer.supported_backends}')\n",
    "# step_mode=m, supported_backends=('torch', 'cupy')\n",
    "\n",
    "device = 'cuda:0'\n",
    "if_layer.to(device)\n",
    "if_layer.backend = 'cupy'  # switch to the cupy backend\n",
    "print(f'if_layer.backend={if_layer.backend}')\n",
    "# if_layer.backend=cupy\n",
    "\n",
    "x_seq = torch.rand([8, 4], device=device)\n",
    "y_seq = if_layer(x_seq)\n",
    "if_layer.reset()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b65840fe",
   "metadata": {},
   "source": [
    "自定义神经元"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f7b6f80",
   "metadata": {},
   "source": [
    "如前所述，SpikingJelly使用充电、放电、重置三个方程来描述脉冲神经元，在 BaseNode 中可以找到对应的代码，单步模式下的前向传播 single_step_forward 函数即是由这3个过程组成："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ba9e14cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# spikingjelly.activation_based.neuron.BaseNode\n",
    "def single_step_forward(self, x: torch.Tensor):\n",
    "    self.neuronal_charge(x)\n",
    "    spike = self.neuronal_fire()\n",
    "    self.neuronal_reset(spike)\n",
    "    return spike"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d22e54af",
   "metadata": {},
   "source": [
    "其中 neuronal_fire 和 neuronal_reset 对绝大多数神经元都是相同的，因而在 BaseNode 中就已经定义了。不同的神经元主要是构造函数和充电方程 neuronal_charge 不同。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3215bcf0",
   "metadata": {},
   "source": [
    "假设我们构造一种平方积分发放神经元，其充电方程为：\n",
    "$$V[t]=f(V[t-1], X[t])=V[t-1]+X[t]^{2}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4f6660bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#实现方式\n",
    "import torch\n",
    "from spikingjelly.activation_based import neuron\n",
    "\n",
    "class SquareIFNode(neuron.BaseNode):\n",
    "    def neuronal_charge(self, x: torch.Tensor):\n",
    "        self.v = self.v + x ** 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "836d9ab5",
   "metadata": {},
   "source": [
    "BaseNode 继承自 MemoryModule。MemoryModule 默认的多步传播，是使用 for t in range(T) 来循环调用单步传播实现的。因此我们定义 neuronal_charge 后， single_step_forward 就已经是完整的了，进而 multi_step_forward 也可以被使用。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af092075",
   "metadata": {},
   "source": [
    "使用平方积分发放神经元进行单步或多步传播："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f44e681c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_seq=tensor([[0.9209],\n",
      "        [0.7835],\n",
      "        [0.4214],\n",
      "        [0.6112]])\n",
      "sif_layer.v[0]=tensor([0.8481])\n",
      "sif_layer.v[1]=tensor([0.])\n",
      "sif_layer.v[2]=tensor([0.1776])\n",
      "sif_layer.v[3]=tensor([0.5511])\n",
      "y_seq=tensor([[0.],\n",
      "        [1.],\n",
      "        [0.],\n",
      "        [0.]])\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "from spikingjelly.activation_based import neuron\n",
    "\n",
    "class SquareIFNode(neuron.BaseNode):\n",
    "\n",
    "    def neuronal_charge(self, x: torch.Tensor):\n",
    "        self.v = self.v + x ** 2\n",
    "\n",
    "sif_layer = SquareIFNode()\n",
    "\n",
    "T = 4\n",
    "N = 1\n",
    "x_seq = torch.rand([T, N])\n",
    "print(f'x_seq={x_seq}')\n",
    "\n",
    "for t in range(T):\n",
    "    yt = sif_layer(x_seq[t])\n",
    "    print(f'sif_layer.v[{t}]={sif_layer.v}')\n",
    "\n",
    "sif_layer.reset()\n",
    "sif_layer.step_mode = 'm'\n",
    "y_seq = sif_layer(x_seq)\n",
    "print(f'y_seq={y_seq}')\n",
    "sif_layer.reset()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5ded7716",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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